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The Contributions Of Digital Applications In Accounting Education to Fraud Control: A Research On Unıversity Curriculum

Year 2024, Volume: 39 Issue: 1, 161 - 179, 02.03.2024
https://doi.org/10.24988/ije.1311949

Abstract

The global effects of digitalization seen all over the world also show themselves in the field of accounting. Although it is foreseen that the accounting profession will change significantly along with the whole world in the digital age, we see that digital applications have already found a wider application area in the field of accounting. The fact that digital applications compatible with technology are more successful than traditional methods, especially in the detection process, causes the use of digital applications more frequently in the detection and prevention of accounting fraud. For this reason, researchers who will take part in fraud auditing should actively benefit from various data analytics methods. Therefore, the competencies required by the digital age should be taken into account in accounting education curricula. In this study, the current curricula of universities were evaluated within the framework of digital informatics courses offered within the education programs, and it has been determined that there are serious deficiencies in this regard. In this direction, it is recommended to review the existing curricula and organize them according to the needs of the digital age.

References

  • Ahmed, Z. H. (2010). Genetic Algorithm for the Traveling Salesman Problem using Sequential Constructive Crossover Operator. International Journal of Biometrics & Bioinformatics (IJBB), 3(6), 96–105.
  • AICPA. (2002). Statement on Auditing Standards No: 99: Consideration of Fraud. 10 Ocak 2022 tarihinde https://us.aicpa.org/content/dam/aicpa/research/standards/auditattest/downloadabledocuments/au-00316.pdf adresinden alındı.
  • Al-Htybat, K., Von Alberti-Alhtaybat, L., & Alhatabat, Z. (2018). Educating digital native for the future: Accounting educators‟ evaluation of the accounting curriculum. Accounting Education, 27(4), 333–357.
  • Altıntaş, N. (2010). Denetimde Hata ve Hile, Sosyal Bilimler Dergisi, 1, 151-161.
  • Association to Advance Collegiate Schools Of Business (AACSB). (2013). Information Technology Skills and Knowledge for Accounting Graduates. International Accounting Accreditation Standard A7. 18 Şubat 2021 tarihinde AACSB: http://www.aacsb.edu/en/accreditation/standards/2013-accounting/learning-andteaching-standards/standard7/ adresinden alındı.
  • Aulia, S. (2020). Vocational Higher Accounting Education in the Digital Era: Critical Review Opportunities and Challenges. In 3rd International Conference on Vocational Higher Education (ICVHE 2018) (pp. 21-26). Atlantis Press.
  • Beckman, J. K., Michel, M. L., Munter, P., Kaiser Venuti, E. (2017). Progress Despite Uncertainty: Results of the AAA/KPMG Survey on Implementation of IFRS into US Accounting Curricula. KPMG Survey on Implementation of IFRS into US Accounting Curricula.
  • Bozkurt, N. (2011). İşletmelerin Kara Deliği Hile, Alfa Yayınları, İstanbul.
  • Burnett, S. (2003). The future of accounting education: A regional perspective. Journal of Education for Business, 78(3), 129-134.
  • Cao, M, R. Chychyla, Stewart, T. (2015). Big data analytics in financial statement audits, Accounting Horizons, 29 (2), 423–429.
  • Chang, C. J., & Hwang, N. R. (2003). Accounting education, firm training and information technology: a research note. Accounting Education, Vol. 12 No. 4, pp. 441-50.
  • Chen, H., Chiang, R.H.L., Storey, V.C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly, 36 (4), 1165–1188.
  • Cory, S.N., & Pruske, K. A. (2012). Necessary skills for accounting graduates: An exploratory study to determine what the profession wants. Proceedings of ASBBS, Vol. 19 No. 1, pp. 208-218.
  • Çalış, Y.E., Keleş, E., Engin, A. (2014). Hilenin Ortaya Çıkarılmasında Bilgi Teknolojilerinin Önemi ve Bir Uygulama, Muhasebe ve Finansman Dergisi, Temmuz, 93-108.
  • Çatıkkaş, Ö., Çalış, Y.E. (2007). İşletmelerde Muhasebe Hilelerinin Önlenebilmesi için Hile Belirtileri, Muhasebe Bilim Dünyası Dergisi, 9 (2).
  • Çağlayan Akay, E. (2018). Ekonometride Yeni Bir Ufuk: Büyük Veri ve Makine Öğrenmesi, Social Sciences Research Journal, 7(2), 41-53.
  • Doğan, S., Kayakıran, D. (2017). İşletmelerde Hile Denetiminin Önemi, Maliye Finans Yazıları, 108, 167-188.
  • Dündar, D. R., Sarıçiçek, İ., Çınar, E., Yazıcı, A. (2021). Kestirimi Bakımda Makine Öğrenmesi: Literatür Araştırması, ESOGÜ Mühendislik Mimarlık Fakültesi Dergisi, 29(2), 256-276.
  • Ernst & Young (EY). (2014). Global Forensic Data Analytics Survey 2014: Mining Big Data to Mitigate Corruption Risk, 13 Mart 2022 tarihinde http://www.ey.com/gl/en/services/assurance/fraud-investigation---dispute-services/eyglobal-forensic-data-analytics-survey-2014 adresinden alındı.
  • Ernst & Young (EY). (2016). Global Forensic Data Analytics Survey 2016. Shifting into Higher Gear: Mitigating Risks and Demonstrating Returns, 13 Mart 2022 tarihinde http://www.ey.com/gl/en/services/assurance/fraudinvestigation---dispute-services/ey-shifting-into-high-gear-mitigating-risks-and-demonstrating-returns adresinden alındı.
  • Gartner. (2014). 2014 IT Glossary. 10 Mart 2022 tarihinde http://www.gartner.com/it-glossary/?s=big+data adresinden alındı.
  • Greenstein, M., & Mckee, T. M. (2004). Assurance practitioners’ and educators’ self-perceived IT knowledge level: an empirical assessment. International Journal of Accounting Information Systems, Vol. 5 No. 2, pp. 213-43.
  • Handoyo, S., & Anas, S. (2019). Accounting education challenges in the new millennium era. Journal of Accounting Auditing and Business, 2(1), 35-46.
  • Jackson, R.B., & Cherrington, J. O. (2001). IT Instruction Methodology and Minimum Competency for Accounting Students. Journal of Information Systems Education, Vol. 12 No. 4, pp. 213-22.
  • Kayıkçıoğlu, S. (2017). Şirketlerin İç Denetim Birimlerinde Hile Denetimi ve Bir Uygulama, Işık Üniversitesi Sosyal Bilimler Enstitüsü, İstanbul.
  • Kelly, J. (2016). Corporate Fraud. A Plus-HKCPA. 7 Mart 2022 tarihinde 1http://app1.hkicpa.org.hk/APLUS/2016/11/pdf/full-Nov.pdf adresinden alındı.
  • KGK. (2013). Bağımsız Denetim Standardı 240, Finansal Tabloların Bağımsız Denetiminde Bağımsız Denetçinin Hileye İlişkin Sorumlulukları, 19 Şubat 2022 tarihinde https://kgk.gov.tr/Portalv2Uploads/files/PDF%20linkleri/standartlar%20ve%20ilke%20kararlar%C4%B1/DENET%C4%B0M%20STANDARTLARI/BDS_240.pdf adresinden alındı.
  • Özkul, U. F. & Pektekin, P. (2009). Muhasebe Yolsuzluklarının Tespitinde Adli Muhasebcinin Rolü ve Veri Madenciliği Tekniklerinin Kullanılması, Muhasebe Bilim Dünyası Dergisi, 4, 57-58.
  • Pincus, K. V., Stout, D. E., Sorensen, J. E., Stocks, K. D., & Lawson, R. A. (2017). Forces for change in higher education and implications for the accounting academy. Journal of Accounting Education, 40, 1-18.
  • PricewaterhouseCoopers (PwC). (2015). February. Data driven—what students need to succeed in a rapidly changing business world. https://www.pwc.com/us/en/faculty-resource/assets/pwc-data-driven-paper-feb2015.pdf
  • Rezaee, Z. & Riley, R. (2010). Financial Statement Fraud Prevention and Detection, John Wiley&Sons, A.B.D.
  • Rezaee, Z., Wang, J., & Lam, B. (2018). Toward the integration of big data into forensic accounting education, Journal of Forensic and Investigative Accounting, 10(1), 87-99.
  • Ryll, L. & Seidens, S. (2019). Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey, Cornell University.
  • Seda, M., Bonita, K. & Kramer, P. (2014). An Examination of the Availability and Composition of Forensic Accounting Education in the United States and Other Countries, Journal of Forensic & Investigative Accounting, 6(1), 1–46.
  • Seethamraju Dr, R. (2010). Information technologies in accounting education.
  • Sledgianowski, D., Gomaa, M., & Tan, C. (2017). Toward integration of Big Data, technology and Information Systems competencies into the accounting curriculum. Journal of Accounting Education, 38, 81–93.
  • Strong, J., & Portz, K. (2015). IT knowledge: What do accounting students think they know? Do you know more than I do? An exploratory study. Review of Business Information Systems (RBIS), 19(2), 39-50.
  • Terzi, S., Kıymetli Şen, İ. (2015). Adli Muhasebede Hilelerin Tespitinde Yapay Sinir Ağı Modelinin Kullanımı, Uluslararası İktisadi ve İdari İncelemeler Dergisi, 14, 477-490.
  • Tsiligiris, V., & Bowyer, D. (2021). Exploring the impact of 4IR on skills and personal qualities for future accountants: a proposed conceptual framework for university accounting education. Accounting Education, 30(6), 621-649.
  • Van Den Bogaerd, M. & Aerts, W. (2011). Applying machine learning in accounting research, Expert Systems with Applications, 38(10), 13414-13424.
  • Vasarhelyi, M., Kogan, A. & Tuttle, B.M. (2015). Big Data in Accounting: An overview, Accounting Horizons, 29(2), 381–396.
  • Voshaar, J., Knipp, M., Loy, T., Zimmermann, J., & Johannsen, F. (2023). The impact of using a mobile app on learning success in accounting education. Accounting Education, 32(2), 222-247.
  • Wang, J., Grace, L., Crumbley, D.L. (2016). Current Availability of Forensic Accounting Education and State of Forensic Accounting Services in Hong Kong and Mainland China, Journal of Forensic and Investigative Accounting, 8(3), 515–534.
  • Yıldız, S., & Demir, V. (2021). Makine Öğrenmesinin Muhasebe ve Finansman Alanında Kullanımı. 20 Ocak 2022 tarihinde https://archive.ismmmo.org.tr/YAYINLAR/e_kitap/20102021_makine_ogrenmesinin_muhasebe_ve_finansman_alaninda_kullanimi_kitapcik.pdf adresinden alındı.
  • Yoon, K., L. Hoogduın, Zhang, L. (2015), Big Data as Complementary Audit Evidence, Accounting Horizons, 29(2), 43–438.
  • Yücel, G., Adiloğlu, B. (2019). Dijitalleşme- Yapay Zekâ ve Muhasebe Beklentiler, Muhasebe ve Finans Tarihi Araştırmaları Dergisi, 17, 47-60.

Muhasebe Eğitiminde Dijital Uygulamaların Hile Denetimine Katkıları: Üniversite Müfredatlarında Bir Araştırma

Year 2024, Volume: 39 Issue: 1, 161 - 179, 02.03.2024
https://doi.org/10.24988/ije.1311949

Abstract

Dijital çağda tüm dünyayla beraber muhasebe mesleğinin de önemli ölçüde değişeceği öngörülmekte; dijital uygulamaların muhasebede kendine şimdiden daha geniş bir uygulama alanı bulacağı düşünülmektedir. Özellikle hile tespiti konusunda teknolojiyle uyumlu dijital uygulamaların, geleneksel yöntemlere kıyasla daha başarılı olması; muhasebe hilelerinin tespitinde ve önlenmesinde dijital uygulamalara daha sık bir biçimde başvurulmasına neden olmaktadır. Muhasebe alanında hile denetiminde görev yapacak olan meslek mensuplarının, bilişim altyapıları, bilgi teknolojileri ve veri analitiğine olan hakimiyeti olası muhasebe hile ve usulsüzlüklerinin önüne geçilebilmesi adına oldukça önemlidir. Bu nedenle hile denetiminde rol alacak mezunların çeşitli veri analitiği yöntemlerinden aktif bir şekilde yararlanması gerekmektedir. Dolayısıyla, üniversite müfredatlarına hile denetiminde kullanılacak becerilerin dijital çağın gerektirdiği şekilde entegre edilmesi zorunlu hale gelmektedir. Üniversitelerde konuya ilişkin dijital çağa uyumlu müfredatların oluşturulması, güncel müfredata veri analitiği yöntemlerinin ve diğer dijital uygulamalarının eklenmesi, öğrencilerin mesleki alanlarda kullanabilecekleri dijital yetkinliklere henüz mezun olmadan sahip olabilmelerini sağlayacaktır. Söz konusu amaç doğrultusunda yapılan bu çalışmada, Türkiye’de işletme eğitimi veren üniversitelerin hile denetimine katkı sağlayacak uygulamaya dönük yeterlilikleri araştırılmıştır. Çalışmada üniversitelerin güncel müfredatları eğitim programları dahilinde sunulan dijital bilişim dersleri çerçevesinde değerlendirilmiş olup; bu konuda ciddi eksiklikler olduğu saptanmıştır. Bu doğrultuda mevcut müfredatların yeniden gözden geçirilmesi ve dijital çağın gereksinimlerine uygun olarak düzenlenmesi önerilmektedir.

References

  • Ahmed, Z. H. (2010). Genetic Algorithm for the Traveling Salesman Problem using Sequential Constructive Crossover Operator. International Journal of Biometrics & Bioinformatics (IJBB), 3(6), 96–105.
  • AICPA. (2002). Statement on Auditing Standards No: 99: Consideration of Fraud. 10 Ocak 2022 tarihinde https://us.aicpa.org/content/dam/aicpa/research/standards/auditattest/downloadabledocuments/au-00316.pdf adresinden alındı.
  • Al-Htybat, K., Von Alberti-Alhtaybat, L., & Alhatabat, Z. (2018). Educating digital native for the future: Accounting educators‟ evaluation of the accounting curriculum. Accounting Education, 27(4), 333–357.
  • Altıntaş, N. (2010). Denetimde Hata ve Hile, Sosyal Bilimler Dergisi, 1, 151-161.
  • Association to Advance Collegiate Schools Of Business (AACSB). (2013). Information Technology Skills and Knowledge for Accounting Graduates. International Accounting Accreditation Standard A7. 18 Şubat 2021 tarihinde AACSB: http://www.aacsb.edu/en/accreditation/standards/2013-accounting/learning-andteaching-standards/standard7/ adresinden alındı.
  • Aulia, S. (2020). Vocational Higher Accounting Education in the Digital Era: Critical Review Opportunities and Challenges. In 3rd International Conference on Vocational Higher Education (ICVHE 2018) (pp. 21-26). Atlantis Press.
  • Beckman, J. K., Michel, M. L., Munter, P., Kaiser Venuti, E. (2017). Progress Despite Uncertainty: Results of the AAA/KPMG Survey on Implementation of IFRS into US Accounting Curricula. KPMG Survey on Implementation of IFRS into US Accounting Curricula.
  • Bozkurt, N. (2011). İşletmelerin Kara Deliği Hile, Alfa Yayınları, İstanbul.
  • Burnett, S. (2003). The future of accounting education: A regional perspective. Journal of Education for Business, 78(3), 129-134.
  • Cao, M, R. Chychyla, Stewart, T. (2015). Big data analytics in financial statement audits, Accounting Horizons, 29 (2), 423–429.
  • Chang, C. J., & Hwang, N. R. (2003). Accounting education, firm training and information technology: a research note. Accounting Education, Vol. 12 No. 4, pp. 441-50.
  • Chen, H., Chiang, R.H.L., Storey, V.C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly, 36 (4), 1165–1188.
  • Cory, S.N., & Pruske, K. A. (2012). Necessary skills for accounting graduates: An exploratory study to determine what the profession wants. Proceedings of ASBBS, Vol. 19 No. 1, pp. 208-218.
  • Çalış, Y.E., Keleş, E., Engin, A. (2014). Hilenin Ortaya Çıkarılmasında Bilgi Teknolojilerinin Önemi ve Bir Uygulama, Muhasebe ve Finansman Dergisi, Temmuz, 93-108.
  • Çatıkkaş, Ö., Çalış, Y.E. (2007). İşletmelerde Muhasebe Hilelerinin Önlenebilmesi için Hile Belirtileri, Muhasebe Bilim Dünyası Dergisi, 9 (2).
  • Çağlayan Akay, E. (2018). Ekonometride Yeni Bir Ufuk: Büyük Veri ve Makine Öğrenmesi, Social Sciences Research Journal, 7(2), 41-53.
  • Doğan, S., Kayakıran, D. (2017). İşletmelerde Hile Denetiminin Önemi, Maliye Finans Yazıları, 108, 167-188.
  • Dündar, D. R., Sarıçiçek, İ., Çınar, E., Yazıcı, A. (2021). Kestirimi Bakımda Makine Öğrenmesi: Literatür Araştırması, ESOGÜ Mühendislik Mimarlık Fakültesi Dergisi, 29(2), 256-276.
  • Ernst & Young (EY). (2014). Global Forensic Data Analytics Survey 2014: Mining Big Data to Mitigate Corruption Risk, 13 Mart 2022 tarihinde http://www.ey.com/gl/en/services/assurance/fraud-investigation---dispute-services/eyglobal-forensic-data-analytics-survey-2014 adresinden alındı.
  • Ernst & Young (EY). (2016). Global Forensic Data Analytics Survey 2016. Shifting into Higher Gear: Mitigating Risks and Demonstrating Returns, 13 Mart 2022 tarihinde http://www.ey.com/gl/en/services/assurance/fraudinvestigation---dispute-services/ey-shifting-into-high-gear-mitigating-risks-and-demonstrating-returns adresinden alındı.
  • Gartner. (2014). 2014 IT Glossary. 10 Mart 2022 tarihinde http://www.gartner.com/it-glossary/?s=big+data adresinden alındı.
  • Greenstein, M., & Mckee, T. M. (2004). Assurance practitioners’ and educators’ self-perceived IT knowledge level: an empirical assessment. International Journal of Accounting Information Systems, Vol. 5 No. 2, pp. 213-43.
  • Handoyo, S., & Anas, S. (2019). Accounting education challenges in the new millennium era. Journal of Accounting Auditing and Business, 2(1), 35-46.
  • Jackson, R.B., & Cherrington, J. O. (2001). IT Instruction Methodology and Minimum Competency for Accounting Students. Journal of Information Systems Education, Vol. 12 No. 4, pp. 213-22.
  • Kayıkçıoğlu, S. (2017). Şirketlerin İç Denetim Birimlerinde Hile Denetimi ve Bir Uygulama, Işık Üniversitesi Sosyal Bilimler Enstitüsü, İstanbul.
  • Kelly, J. (2016). Corporate Fraud. A Plus-HKCPA. 7 Mart 2022 tarihinde 1http://app1.hkicpa.org.hk/APLUS/2016/11/pdf/full-Nov.pdf adresinden alındı.
  • KGK. (2013). Bağımsız Denetim Standardı 240, Finansal Tabloların Bağımsız Denetiminde Bağımsız Denetçinin Hileye İlişkin Sorumlulukları, 19 Şubat 2022 tarihinde https://kgk.gov.tr/Portalv2Uploads/files/PDF%20linkleri/standartlar%20ve%20ilke%20kararlar%C4%B1/DENET%C4%B0M%20STANDARTLARI/BDS_240.pdf adresinden alındı.
  • Özkul, U. F. & Pektekin, P. (2009). Muhasebe Yolsuzluklarının Tespitinde Adli Muhasebcinin Rolü ve Veri Madenciliği Tekniklerinin Kullanılması, Muhasebe Bilim Dünyası Dergisi, 4, 57-58.
  • Pincus, K. V., Stout, D. E., Sorensen, J. E., Stocks, K. D., & Lawson, R. A. (2017). Forces for change in higher education and implications for the accounting academy. Journal of Accounting Education, 40, 1-18.
  • PricewaterhouseCoopers (PwC). (2015). February. Data driven—what students need to succeed in a rapidly changing business world. https://www.pwc.com/us/en/faculty-resource/assets/pwc-data-driven-paper-feb2015.pdf
  • Rezaee, Z. & Riley, R. (2010). Financial Statement Fraud Prevention and Detection, John Wiley&Sons, A.B.D.
  • Rezaee, Z., Wang, J., & Lam, B. (2018). Toward the integration of big data into forensic accounting education, Journal of Forensic and Investigative Accounting, 10(1), 87-99.
  • Ryll, L. & Seidens, S. (2019). Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey, Cornell University.
  • Seda, M., Bonita, K. & Kramer, P. (2014). An Examination of the Availability and Composition of Forensic Accounting Education in the United States and Other Countries, Journal of Forensic & Investigative Accounting, 6(1), 1–46.
  • Seethamraju Dr, R. (2010). Information technologies in accounting education.
  • Sledgianowski, D., Gomaa, M., & Tan, C. (2017). Toward integration of Big Data, technology and Information Systems competencies into the accounting curriculum. Journal of Accounting Education, 38, 81–93.
  • Strong, J., & Portz, K. (2015). IT knowledge: What do accounting students think they know? Do you know more than I do? An exploratory study. Review of Business Information Systems (RBIS), 19(2), 39-50.
  • Terzi, S., Kıymetli Şen, İ. (2015). Adli Muhasebede Hilelerin Tespitinde Yapay Sinir Ağı Modelinin Kullanımı, Uluslararası İktisadi ve İdari İncelemeler Dergisi, 14, 477-490.
  • Tsiligiris, V., & Bowyer, D. (2021). Exploring the impact of 4IR on skills and personal qualities for future accountants: a proposed conceptual framework for university accounting education. Accounting Education, 30(6), 621-649.
  • Van Den Bogaerd, M. & Aerts, W. (2011). Applying machine learning in accounting research, Expert Systems with Applications, 38(10), 13414-13424.
  • Vasarhelyi, M., Kogan, A. & Tuttle, B.M. (2015). Big Data in Accounting: An overview, Accounting Horizons, 29(2), 381–396.
  • Voshaar, J., Knipp, M., Loy, T., Zimmermann, J., & Johannsen, F. (2023). The impact of using a mobile app on learning success in accounting education. Accounting Education, 32(2), 222-247.
  • Wang, J., Grace, L., Crumbley, D.L. (2016). Current Availability of Forensic Accounting Education and State of Forensic Accounting Services in Hong Kong and Mainland China, Journal of Forensic and Investigative Accounting, 8(3), 515–534.
  • Yıldız, S., & Demir, V. (2021). Makine Öğrenmesinin Muhasebe ve Finansman Alanında Kullanımı. 20 Ocak 2022 tarihinde https://archive.ismmmo.org.tr/YAYINLAR/e_kitap/20102021_makine_ogrenmesinin_muhasebe_ve_finansman_alaninda_kullanimi_kitapcik.pdf adresinden alındı.
  • Yoon, K., L. Hoogduın, Zhang, L. (2015), Big Data as Complementary Audit Evidence, Accounting Horizons, 29(2), 43–438.
  • Yücel, G., Adiloğlu, B. (2019). Dijitalleşme- Yapay Zekâ ve Muhasebe Beklentiler, Muhasebe ve Finans Tarihi Araştırmaları Dergisi, 17, 47-60.
There are 46 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Articles
Authors

Gökçe Sinem Erbuğa 0000-0003-1604-4668

Mehmet İlker Karakelleoğlu 0000-0001-6708-0234

Early Pub Date February 9, 2024
Publication Date March 2, 2024
Submission Date June 9, 2023
Acceptance Date November 3, 2023
Published in Issue Year 2024 Volume: 39 Issue: 1

Cite

APA Erbuğa, G. S., & Karakelleoğlu, M. İ. (2024). Muhasebe Eğitiminde Dijital Uygulamaların Hile Denetimine Katkıları: Üniversite Müfredatlarında Bir Araştırma. İzmir İktisat Dergisi, 39(1), 161-179. https://doi.org/10.24988/ije.1311949
İzmir Journal of Economics
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